According to a recent article by Grant Gross of the CIO Magazine, “Many C-suite execs have lost confidence in IT, including CIOs.”

It all boils down to IT organizations’ inability to cope-up with change and evolving business technological demands. But the other crucial factor is how IT leaders fail to evolve their own complex and cumbersome processes related to IT service management. Processes like, helpdesk, access provisioning, service monitoring, patch management, software updates, among other basic IT services are defunct and have become a major source of frustration for end-users, leading C-levels to lose confidence with the IT organization.

Like technology and infrastructure, IT processes must evolve to keep-up with the changing times, cope-up with emerging technologies, and manage the expectations and the demands of the business. Some IT processes have been stagnant for many years and even decades. These defunct and obsolete processes often cause end-user frustrations, bleed inefficiencies, and impact the productivity and engagement of employees—and therefore the company’s bottom line.

The good news is, it’s not too late. The over-zealous drive and business appetite of many organizations to implement Gen AI, could redeem IT‘s credibility. In fact, according to Gartner, 74% of CEOs have AI in their agenda. But IT leaders must be intentional and strategic in using it to improve and reengineer bureaucratic IT processes first—then, showcase what this technology can do, before rolling it out to the business.

Gartner's VP of Research, Christie Struckman in her keynote, “How AI Will Change the IT Department” during the Gartner Symposium 2024, stressed that, “Be a great consumer of AI in IT, so you can be a great producer of AI for the enterprise.”

What is IT Process Management?

IT Process Management refers to the structured approach of planning, executing, monitoring, and optimizing key IT processes to ensure that technology services are delivered efficiently and aligned with business goals. It involves coordinating people, technology, and resources to ensure that IT operations provide the optimal support to organizational objectives, deliver value, and minimize risks. Failing to continuously improve these processes is a mortal sin.

Incident and problem management processes aim to minimize service disruptions and prevent recurring IT issues. Configuration, change, and release management ensure that IT assets and deployments are properly controlled. Service level and financial management processes align IT services with business expectations and promote cost transparency. Capacity, availability, and disaster recovery are essential to ensuring that IT infrastructure, applications, and services meet performance demands, remain highly available and resilient, and protect sensitive information—creating a secure, efficient, resilient, and reliable IT environment. The most crucial element is the continuous improvement process, intended to be the "ring that rules them all." Unfortunately, many IT organizations struggle to implement it effectively, as they remain preoccupied with daily firefighting.

Some of the core IT processes management frameworks commonly used today are ITIL (Information Technology Infrastructure Library), COBIT (Control Objectives for Information and Related Technologies), and ISO 20000. The overarching goal of these frameworks is to optimize service delivery, maintain system stability, and to continuously improve IT operations to meet the ever-evolving business demands. While most IT organizations have deployed some of these processes to a certain extent, no one has ever implemented all of them successfully. This is one of those utopian IT concepts that no organizations have reached 100%. Also, most of these IT processes management frameworks are old and have not caught-up with time. So, in the modern era of AI, tech leaders must consider the following 10 philosophies, paradigms, and principles of IT process management and incorporate them into their operating models to regain the trust of the C-Levels in the IT organization.

P11: Plan Ahead

“Failing to plan is planning to fail.” — Benjamin Franklin

Effective planning is crucial for aligning IT initiatives with business goals. In the AI era, business and tech leaders must anticipate the impact of AI on people, operations, resources, and strategic direction, ensuring that technology investments align with long-term business objectives.

The history of digital transformation teaches us that companies that fail to plan and adapt the technological trends were left behind. Blockbuster, Kodak, Nokia, and Sears are prime examples. AI will redefine the new world business dynamics, and companies that don’t embrace it today will struggle to compete tomorrow. Developing an AI strategy now will help organizations to stay ahead of the curve.

The AI era is characterized by speed of execution, agility, and immediate results; three things that most IT organizations lack. So, tech leaders must consciously take advantage of AI to reverse the situation by incorporating it as key strategy to to fix IT processes that are bureaucratic, inefficient, and that causes typical end-user frustrations.

By using AI-based planning system, IT organizations can take advantage of a structured approach to identify challenges and opportunities early on, prioritize, prescribe the necessary course of action, and craft creative ways to use agentic systems to improve the overall throughput and efficiency of the different targeted processes that will eventually result in improved profitability and competitiveness of the business.

P12: Prioritize

"The key is not to prioritize what's on your schedule, but to schedule your priorities." — Stephen Covey

Prioritization is the process of identifying the most critical tasks to achieve a goal. It is the structured thinking of taking actions to what must be done first according to the importance of their desired output in the grand scheme of things. Effective prioritization can improve time management, business continuity, security, profitability, employee satisfaction, and technically anything under the sun. It ensures that resources are allocated to activities that drive business value. Without a proactive strategy and investment prioritization related to AI assimilation and adoption, organizations can miss potential innovation that this game-changing technology can bring, to keep up with the evolving business requirements and highly competitive economy.

Those who still think that AI is just a fad, are similar to those people who still thinks that the world is flat. IT leaders must start in their own backyard and fix their own processes first, like AI-based employee on-boarding, AI-based self-updating CMDB (Configuration Management Database), AI Helpdesk agents, AI-IT service monitoring, AI-cybersecurity systems to combat AI-cyber-attacks, AI-based self-healing systems, among many other core IT processes.

For businesses and tech leaders who haven’t prioritized AI yet in their agenda, results will be the litmus test in the coming years — unfortunately, it may be a bit too late to recover.

P13: People-Centric AI Systems

"Algorithms are opinions embedded in code. AI will only be people-centric if we ensure it doesn't reinforce existing biases and inequalities." — Cathy O'Neil

With the aid of AI, we can automate many mundane and repetitive tasks and boost our processes. But, on the flip side—we need to humanize IT organizations more. Humanocracy, is a concept by Gary Hamel and Michele Zanini, promoting the decentralization of traditional hierarchical structures to empower employees and foster innovation. It enables a culture where people are prioritized, making organizations more adaptable and resilient.

Most AI solutions are designed to have a direct impact on employees and customers. While technologies are primarily focused in enhancing productivity to contribute to the organization's bottom line. We can take advantage of solutions like sentiments analysis to improve the overall user experience and engagement.

In the past couple of years, when you call your bank’s Helpdesk, you either get transferred to an agent in India or the Philippines. And oftentimes, while the agents are trying hard to help you, most of the time you still feel disgruntled and frustrated because of accent, inability of the agent to really understand your predicament, or you are simply in a bad mood already since they are eating a lot of your time to do something basic. A lot Helpdesk operations have already incorporated AI and has immensely improved their efficiencies and NPS (Net Promoter Score).

Nowadays, you can simply chat a with a robot and get the results in a few minutes after a few Q&As. In this sense, I particularly believe that AI has already surpassed humans in dealing with simple and mundane Helpdesk issues such as resetting password, blocking or unblocking something, scheduling and rescheduling, or asking for a simple information.

P14: Punctual-Automated CMDB Powered by AI

"A self-updating CMDB isn't just a database; it's the pulse of your IT ecosystem.”

A Punctual-Automated CMDB (Configuration Management Database) powered by AI will revolutionize the traditional configuration management process by combining real-time data collection with advanced AI capabilities to create a self-sustaining and intelligent system. In this model, AI algorithms continuously monitor and analyze the IT environment, detecting and documenting changes in configuration items (CIs) as they happen. The system is "punctual" because it always maintains an up-to-date state, responding to changes instantaneously through automation. AI enhances this process by learning patterns from historical data, predicting potential configuration changes, and identifying risks before they materialize, making the CMDB more proactive and predictive.

This AI-driven automatic CMDB allows for smart anomaly detection, reducing configuration drift and improving accuracy. For example, if an unauthorized change is made to a server configuration or an unexpected CI relationship emerges, AI can quickly flag it for review or even automatically revert it to a known good state. This proactive approach ensures that the CMDB remains a trustworthy source of truth for the IT environment, supporting other ITSM processes like incident management, where accurate and timely configuration data is crucial for diagnosing problems. AI also provides insights into hidden relationships between CIs, improving impact analysis and enabling better planning for future changes.

The integration of AI into a punctual-automated CMDB not only makes the configuration management process faster but also more intelligent and scalable. AI algorithms can continuously optimize the CMDB by identifying redundant CIs, optimizing resources, and suggesting improvements based on evolving IT infrastructure and business needs. This leads to better governance, reduced operational overhead, and a CMDB that evolves in real-time.

P15: Performance Measurement Turbo-charged by AI

“Measure what matters.” — John Doerr

You can’t improve what you can’t measure. Establishing OKRs (Objectives and Key Results) to track IT performance is crucial for assessing process effectiveness. OKRs promote alignment and transparency across the organization. By focusing on key results, IT leaders can prioritize what matters, ensuring that resources are directed toward achieving meaningful outcomes that contribute to business success.

AI-driven analytics can offer real-time insights, enabling proactive course corrections and enhancements before issues escalate. Measuring IT infrastructure uptime is foolish if users are complaining that your system is unusable. AI can turbo-charge monitoring systems, KPIs, and OKRs so IT folks can focus on value creation and bottom-line results.

Detecting operational deviations to perform course-corrections early on, preventing project stoppers to avoid project delays, and providing insights on what services can be canceled are some activities that AI can enhance.

P16: Process Optimization Must Come Prior to Automation

“There is nothing so useless as doing efficiently that which should not be done at all.” — Peter Drucker

AI can optimize workflows by automating repetitive tasks, but IT leaders should first assess whether these tasks are necessary. Eliminating redundant processes and focusing on meaningful automation is more valuable than merely increasing efficiency.

Streamlining processes reduces bureaucracy and fosters a more agile environment. By eliminating non-value-adding activities, organizations can focus on core competencies and drive innovation. For example, instead of automating multiple layers of access approval, evaluate if it can be reduced to one. Then, automate the process to have access approver respond live through chat or SMS. Once, approvals are secured, provisioning of the service can be automated, and users are notified.

P17: Prompt & Proactive Problem Management

"Clearly prevention is better than cure, but when you’re sick, you need a pill to bring temporary relief."

AI can enhance proactive problem management by predicting and preventing potential issues. However, dealing with day-to-day operational challenges still requires prompt responses to ensure business continuity. When incidents arise, swift resolution and root cause analysis are crucial. They are relevant input to drive proactive problem management, which involves not just responding to issues, but also implementing preventive measures to reduce future occurrences.

Prevent first, mitigate second, and remediate fast. Problems and incidents must be prevented by attacking their root causes. If they cannot be prevented, at least, try to reduce their frequency. And when incidents persist, have a process ready to mitigate their impact by implementing workarounds, and having a business continuity plan in place is imperative. Combining the power of analytics, AI, and automation, IT organizations now have all the ingredients to create self-healing systems, instead of relying on manual monitoring and troubleshooting.

P18: Prepare and Test Your Business Continuity Plan

"A Business Continuity Plan that is not tested, is the same as not having it all."

Developing robust business continuity plan is essential for resilience against business disruptions. AI can simulate scenarios and optimize response strategies, but preparation and practice are key.

Testing continuity plans regularly ensures that businesses are well-prepared for unexpected disruptions, minimizing downtime and ensuring rapid recovery. A BCP that is not tested, is as worst as not having one.

P19: Policy Compliance

“When you realize the price of a breach, compliance becomes cheap.”

Compliance ensures that organizations meet regulatory standards and protect against legal, financial, and reputational risks. Policies governing AI ethics, data protection, and usage are critical in minimizing risks associated with AI deployment. Establishing strong compliance frameworks also builds trust, positioning organizations as responsible adopters of AI technology.

Laws like the EU AI Act focuses on ensuring transparency, risk management, and ethical AI use. It introduces requirements for developers of high-impact AI models, such as risk mitigation and incident reporting, while restricting certain uses, like real-time biometric surveillance in public spaces, unless justified by security concerns.

Regulation is necessary to prevent harm, and ill use of AI, but it must also remain flexible to accommodate the rapid evolution of the technology. Striking this balance will require collaboration between governments, companies, and civil society to ensure responsible development while encouraging innovation. Organizations poking around with AI must start drafting compliance guardrails before it turns into a Frankenstein.

P20: Proactive Continuous Improvement

“Don’t just react—anticipate. ”

Traditional Continuous Improvement process is often associated with methodologies such as Kaizen (a Japanese concept meaning "change for the better"), Lean (focused on eliminating waste), and Six Sigma (focused on reducing defects and variability). In IT and service management, it is integrated into frameworks like ITIL (Information Technology Infrastructure Library) and ISO standards like ISO 9001 (Quality Management System) and ISO 20000 (IT Service Management), which emphasize continual service and quality improvements. By continually refining and optimizing processes, organizations can adapt to changing market conditions, improve customer satisfaction, and achieve long-term success in a sustainable manner.

However, traditional Continuous Improvement processes is still reactive. Typically, you wait to detect improvement opportunities before taking actions. You fix things when they are broken. In Proactive Continuous Improvement (PCI), on the other hand, IT leaders take a forward-looking stance — fixing things before they break. By anticipating potential areas of enhancement and innovation, it fosters a consistent and evolutionary progressive development of processes and services. The PCI approach leverages data analytics, performance metrics, customer feedback using sentiments analysis, and different machine learning techniques to identify opportunities that can provide strategic value over time and suggest improvement actions at a prescribed and opportune time. The integration of progressive thinking allows businesses to stay ahead of the curve and adapt to shifting industry trends and technologies, as well as economic, political, environmental, and other factors.

The adoption of PCI also facilitates a stronger alignment between IT and business strategies. It allows organizations to remain competitive by continuously refining their operations, not just to meet existing requirements, but to set new benchmarks for performance and innovation. The process involves key stages like setting improvement visions, analyzing gaps, prioritizing strategic initiatives, implementing changes, and reviewing outcomes—creating a closed-loop system of ongoing enhancement.

Conclusion:

In the exhilarating and rapidly evolving world, where much evolved AI and robots, (like Optimus) will soon become a typical household appliance, we are living in a very exciting tipping-point of technological revolution. Those who think that AI is still a science fiction, will be left behind. Those who are not leveraging AI, preparing for it, and incorporating it as a core strategy will dreadfully regret their passiveness in the next few years. IT leaders who are not leveraging AI to improve bureaucratic and inefficient IT processes, will never be successful in deploying AI in the business. AI can turbo-charge processes, but leaders need to evaluate which ones can be eliminated and optimized first. As technology evolves, processes must evolve and catch-up.

Prevent first, mitigate second, and remediate fast. With AI, we now have the power to anticipate rather than just react.